Some of today's most significant challenges in urban environments concern individual mobility and rapid parcel delivery. With the surge of e-commerce and the ever-increasing volume of goods to be handled, new logistic solutions are in high demand. The share-a-ride problem (SARP) was proposed as one such solution, combining people and parcel transportation in taxis. This is an NP-hard problem and thus obtaining optimal solutions can be computationally costly. In this paper, we work with a variation of SARP for ride-hailing systems, which can be formulated as a multi-depot open generalised vehicle routing problem with time windows. We present and solve a mixed-integer linear programming (MILP) formulation for this problem that bundles requests together, and we compare its results to a previously proposed two-stage method. The latter solves the so-called freight insertion problem (FIP) in the second stage, for which we consider two versions, and the problem consists of inserting parcels into predefined passenger routes obtained in the first stage. We tested the methods in three sets of instances. The developed bundle-based approach outperformed both FIP versions in solution quality and in the service of parcels. Our method also compares favourably when it comes to reducing the amount of deadheading distance.
翻译:当今城市环境的一些最重大的挑战涉及个人流动性和快速交付包裹。随着电子商务的激增和需要处理的货物数量不断增加,新的后勤解决方案的需求很大。共享问题(SARP)被提出为一种解决办法,将出租车中的人员和包裹运输结合起来。这是一个NP的难题,因此获得最佳解决办法可以计算成本很高。在本文件中,我们采用SARP对乘车系统的一种变通办法,这种办法可以作为一种多端的开放通用车辆行驶和时间窗口的问题来拟订。我们提出并解决了这一问题的混合整数线性编程(MILP)配方,将要求捆绑在一起,并将其结果与先前提出的两阶段方法进行比较。后者解决了第二阶段的所谓货运加装问题,我们为此审议两种版本,问题包括将包裹插入在第一阶段获得的预定客运路线中。我们用三种实例测试了方法。发达的捆绑式办法在将FIP版本的质量与远端办法相比较后,我们的远端办法也比了我们的远端办法。